Databricks raised $5B in equity financing and $2B in debt at a $134B valuation and says its annualized revenue crossed $5.4B for the January quarter, up 65% YoY
Databricks said Monday it has raised $5 billion in funding and $2 billion in new debt capacity at a $134 billion valuation.
CNBCJordan Novet
Context & Ripple Effects
This financing follows Databricks' planned $4B Series L at the same $134B valuation in December, indicating that the company has sustained investor support while reporting a higher annualized revenue run rate.
It also comes after reports that Databricks had added $1.8B in fresh debt ahead of a potential IPO, making the latest package part of a broader shift toward using both equity and debt to fund its next phase.
First-order effects
Databricks adds $5B of equity capital and $2B of debt capacity while retaining a $134B valuation, expanding its financial flexibility without a reported valuation reset.
The company’s disclosed $5.4B annualized revenue rate and 65% growth give investors a current operating marker against which to assess that valuation.
Second-order effects
The round sets a demanding private-market benchmark for other data and AI platform companies seeking late-stage funding: growth and revenue scale are increasingly central to raising large sums at premium valuations.
Greater access to debt alongside equity can widen the funding gap between established platforms with recurring revenue and smaller rivals that must rely more heavily on equity financing.
Third-order effects
If this financing pattern persists, late-stage AI and data infrastructure companies may increasingly be funded as durable enterprise platforms through blended capital structures rather than successive equity rounds alone.
That would reinforce capital concentration around a smaller group of companies able to pair high growth with enough revenue scale to support both investor confidence and lender participation.
The trend: AI and data-platform financing is moving toward larger, blended equity-and-debt capital stacks for companies that can demonstrate substantial recurring revenue growth.
Databricks just raised at 25x in the private market only one public software company is traded above that, Palantir at 37x
@databricks
@databricks on x
Today we announced Databricks Q4 results: * Surpassing $5.4B revenue run-rate, growing >65% year-over-year * Delivering positive free cash flow over the last 12 months * Crossing $1.4 billion revenue run-rate for our AI products Databricks is also completing investments in the [i…
@firstadopter
Tae Kim on x
It's almost as if AI can help SaaS companies provide more value and insights to their customers. Crazy. That said, business models will likely transition from seat-based to usage-based pricing.
@advisercounsel
Max Schatzow on x
If Databricks can raise $5B in private markets at a valuation of $134B, I just don't see the point of ever going public anymore. I also couldn't tell you what they actually do.
@jaminball
Jamin Ball on x
Beast of a company. Accelerated in Q2, Q3 and Q4!
@dee_bosa
Deirdre Bosa on x
Databricks raised $7 billion because the smartest investors in the room were getting year 2000 vibes @alighodsi isn't predicting a crash but he's preparing for one [video]
@mukund
M Mohan on x
If public this would be $120B
@alighodsi
Ali Ghodsi on x
I now constantly get questions about the SAAS meltdown, role of AI, system of records etc. I don't have an answer to all these. But I do know that we saw an acceleration in our business in Q2, Q3, and now finished the year with accelerating Q4. The question is, why? Short
@edzitron
Ed Zitron on x
So this whole “80% of databases are being built by AI agents” is interesting, in that it's all from Databricks' acquisition of Neon in May 2025 - and hasn't changed since June 2025. This is an egregious overstatement! https://www.linkedin.com/... https://www.databricks.com/... […
@sarahdingwang
Sarah Wang on x
One of the most impressive and (dare I say) underrated aspects of @databricks is that @alighodsi and his team have been focused on building a platform for data + AI from day 1. This is why they're not ‘the Spark company’ or even Spark + SQL. imho the fact that Lakebase Postgres
@dee_bosa
Deirdre Bosa on x
Databricks is showing us what the AI economy looks like under the hood... and its BOOMING. 80% of databases on their platform are being built by AI agents. Which means AI is building more enterprise software than humans are. We talk to @alighodsi today. Link to livestream